Combing MATLAB with Amazon Web Services to produce highly scale cloud based applications

James P. Doherty

AOG 2016

j

• MATLAB is the world’s leading scientific computing software. • Amazon Web Services is the world’s leading cloud computing platform. • Combining the two enables applications written in MATLAB to access

almost unlimited computational power and durable data storage. This enables us to:

– solve extremely large computational problems rapidly, without the cost of setting up and maintaining a super computer or a cluster.

– deploy highly available MATLAB based web applications that can be accessed by one or one-million users.

– centralise data storage and streamline workflows.• By using the MATLAB Complier and MATLAB SDK toolbox, this can be

done without re-writing any MATLAB code.

Overview

Jmjame1james.doherty@uwa.edu.au

j

• What is the cloud?• AWS• Why cloud is useful to engineering design?• Example application• Architecture behind the application• Conclusions

Outline

Jmjame1james.doherty@uwa.edu.au

j

Somewhere at the other end of your internet connection – a place where you can access apps and services, and where your data can be stored securely. The cloud is a big deal for three reasons:

– No effort on your part to maintain or manage it.– You can access cloud-based applications and services from anywhere – all you

need is a device with an Internet connection.– It's effectively infinite in size, so you don't need to worry about it running out of

capacity and scales on demand so you only pay for what you use.

Some of the major cloud computing companies

What is the Cloud?

Jmjame1james.doherty@uwa.edu.au

Traf

fic/c

ompu

te

pow

er

Provision for peak

Wasted $$

Scale on demand

Victorian Racing Club

Jan Dec

Melbourne Cup

j

Every day, AWS adds enough new server capacity to support all of Amazon’s global infrastructure when it was a $7B retailer

AWS

Jmjame1james.doherty@uwa.edu.au

j

• Access virtually unlimited computing power– Specific machines for RAM, storage, or GPU– For highly parallel tasks, like Monte Carlo or

optimisation problems you can spread work across 1000s of machines

– Highly durable data storage

• Enhanced QA/QC– Desktop applications are hard to control and maintain.

With cloud you have one fully QA ed copy of an application.

– Access from anywhere.– Improved project management and collaboration.

• Secure intellectual property

What role can cloud computing play in engineering design?

Jmjame1james.doherty@uwa.edu.au

j

The application: design foundations for offshore oil and gas infrastructure

Jmjame1james.doherty@uwa.edu.au

Source: Norske Hydro

Pazfloor, Angola. Image courtesy of Subsea 7

Particular challenges• Weak soils• Complex load history• Capacity depends on

load history• Must simulate many

cases

j

Acknowledgements

Ali AmodioCarl ErbrichDave WilliamsFraser BransbyHenry KrisdaniMarcelo SilvaMike O’NeillPhil WatsonSusan GourvenecDave WhiteMark Randolph

Jmjame1james.doherty@uwa.edu.au

j

Process• Input soil properties• Consolidation analysis to get change in effective stress under dead loads• Change in effective stress leads to change in soil strength• Using modified strength, conducted a series of H-V capacity calculations

for different effective widths and CLR values• Compare with 1000’s of load cases• Document

Offshore foundation design

Jmjame1james.doherty@uwa.edu.au

H

Vseabed

Image courtesy of Susan Gourvenec

j

Job details

Jmjame1james.doherty@uwa.edu.au

j

Paste input into excel like tables

Jmjame1james.doherty@uwa.edu.au

j

Solve the consolidation problem

Jmjame1james.doherty@uwa.edu.au

j

H-V capacity problem

Jmjame1james.doherty@uwa.edu.au

j

Example output

Jmjame1james.doherty@uwa.edu.au

Computationally intensive; up to 30 minutes per run

j

More output from HV

Jmjame1james.doherty@uwa.edu.au

j

Paste in 1000s of load cases

Jmjame1james.doherty@uwa.edu.au

j

Compute FoS

Jmjame1james.doherty@uwa.edu.au

j

System architecture

Jmjame1james.doherty@uwa.edu.au

All AWS regions have at least two physically separate “availability zones”, with a guaranteed uptime of 99.95%.

Design your system so that if one zone goes down, the system still works as normal

j

System architecture

Jmjame1james.doherty@uwa.edu.au

All AWS regions have at least two physically separate “availability zones”, with a guaranteed uptime of 99.95%

Some services reside in specific availability zones

Computer servers

j

System architecture

Jmjame1james.doherty@uwa.edu.au

All AWS regions have at least two physically separate “availability zones”, with a guaranteed uptime of 99.95%

Others automatically work across zones

j

System architecture

Jmjame1james.doherty@uwa.edu.au

User fills in a web form and hits “run” and send a package of data to the web server

j

System architecture

Jmjame1james.doherty@uwa.edu.au

The web server sends the package to a data base for storage

Web server is in constant communication with data base to keep user informed of status of the job

Job queueing

j

System architecture

Jmjame1james.doherty@uwa.edu.au

The web server sends meta data to a queue

Status=queueing

Job queueing

j

System architecture

Jmjame1james.doherty@uwa.edu.au

An application server reads the meta data from a queue

Job queueing

Status=queueing

j

System architecture

Jmjame1james.doherty@uwa.edu.au

Using this meta data, and the MATLAB Database Toolbox the application server can get the full input data object from the database and can then run the job

Job Running

j

System architecture; more than serving up a web page!

Jmjame1james.doherty@uwa.edu.au

After the job finishes and app server generates output data and writes this to the database using the MATLAB Database Toolbox. Images are stored in S3

Status=Complete

Job Complete

j

System architecture

Jmjame1james.doherty@uwa.edu.au

EC2 instances with the following• MATLAB Runtime Complier

Library (MCR)• Your complied MATLAB code as

a dll• A wrapper function that can read

from SQS and call the dll

Then from this, create an Amazon Machine Image (AMI).

Can then “spin up” as many EC2 instances based on this AMI

The computational engine(s)

j

Example with eight App servers

Jmjame1james.doherty@uwa.edu.au

j

Example with sixteen App servers

Jmjame1james.doherty@uwa.edu.au

j

Cloud computing offers opportunities to access massive compute power and gives flexibility and freedom to a workforce. It also assists with QA and QC and helps secure valuable IP.• This has been demonstrated by developing the Fugro AG shallow

foundation design package, BearCon.• The web application combines several design processes into a single

workflow, resulting in a large reduction in manual data processing, making design activities more efficient.

• The scaling capability of cloud based computing will allow large volumes of foundation design calculations to be conducted. This will allow a range of design options to be explored, resulting in optimised foundation solutions. i.e. better engineering design.

Reliability based design can be developed on the back of this. – 2000 Monte Carlo simulations of a calculations that takes 5 minutes, would

take 1 week on a single machine.– Or, using 200 machines (say AWS M3 instances at 15 cents per hr), would get

the job done in around 48 minutes for $30.

Conclusions

Jmjame1james.doherty@uwa.edu.au

j

• By compiling MATLAB into dll using the Complier and SDK toolbox, MATLAB can be seamlessly combined with AWS.

• The MATLAB Database Toolbox simplifies data storage and integration of the data into MATLAB algorithms. Found to be fast and reliable.

• Even though MATLAB was one of about 8-10 different technologies used it was probably the most important in enabling an application such as BearCon to be written.

Conclusions

Jmjame1james.doherty@uwa.edu.au